Epidemo A Machine Learning Regression-Based
Abstract
In recent years, the world has witnessed the devastating consequences of disease outbreaks, highlighting the urgent need for effective epidemic management. An epidemic signifies the rapid transmission of illness to a substantial portion of a population within a short timeframe. The proposed system offers a proactive approach to this challenge by leveraging advanced Machine Learning (ML) regression tools. By analyzing diverse data sources such as historical disease trends, environmental conditions, and human behaviors, the system predicts the onset and spread of diseases, providing crucial early warnings for public health authorities and communities. Through timely implementation of preventive measures informed by these forecasts, authorities can mitigate the impact of epidemics, safeguard public health, and alleviate strain on healthcare systems. This proactive strategy underscores the importance of early intervention and data-driven approaches in combating and controlling disease outbreaks.
Keywords:
Epidemic ManagementPublished
Issue
Section
License
Copyright (c) 2024 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Rohan Malka, Jerin Joseph Abraham, Jobcy Johnson, Sobin Saju, Febin Sam Philip, Aju Mathew George, S.N.Kumar , Green Waste Utilization for Sustainable Energy Engineering Application: A Path towards Green Circular Economy , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Ashish George, Fida Fathima N, Aswin Kumar A, Nishok Perumal A , Lini Ickappan, GITSHUB - A COMPREHENSIVE PLATFORM FOR ACADEMIC NETWORKING, MENTORSHIP, AND CAREER DEVELOPMENT , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Nivedh Mohanan, Subhash P C, Subin K S, Subin V Ninan, Elisabeth Thomas, S N Kumar, A Qualitative Study on Segmentation of MR Images of Brain for Neuro Disorder Analysis , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
You may also start an advanced similarity search for this article.
